{"product_id":"evolutionary-optimization-algorithms-biologically-inspired-and-population-based-approaches-to-computer-intelligence-9780470937419","title":"Evolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence","description":"\u003cp\u003e • Author(s): Dan Simon\u003cbr\u003e • Publisher: Wiley\u003cbr\u003e • Publisher Imprint: Wiley\u003cbr\u003e • BISAC: Discrete Mathematics\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cb\u003eA clear and lucid bottom-up approach to the basic principles of evolutionary algorithms\u003c\/b\u003e   \u003c\/p\u003e\u003cp\u003eEvolutionary algorithms (EAs) are a type of artificial intelligence. EAs are motivated by optimization processes that we observe in nature, such as natural selection, species migration, bird swarms, human culture, and ant colonies. \u003c\/p\u003e\u003cp\u003eThis book discusses the theory, history, mathematics, and programming of evolutionary optimization algorithms. Featured algorithms include genetic algorithms, genetic programming, ant colony optimization, particle swarm optimization, differential evolution, biogeography-based optimization, and many others. \u003c\/p\u003e\u003cp\u003e\u003ci\u003eEvolutionary Optimization Algorithms:\u003c\/i\u003e  *Provides a straightforward, bottom-up approach that assists the reader in obtaining a clear—but theoretically rigorous—understanding of evolutionary algorithms, with an emphasis on implementation *Gives a careful treatment of recently developed EAs—including opposition-based learning, artificial fish swarms, bacterial foraging, and many others— and discusses their similarities and differences from more well-established EAs *Includes chapter-end problems plus a solutions manual available online for instructors *Offers simple examples that provide the reader with an intuitive understanding of the theory *Features source code for the examples available on the author's website *Provides advanced mathematical techniques for analyzing EAs, including Markov modeling and dynamic system modeling  \u003c\/p\u003e\u003cp\u003eEvolutionary Optimization Algorithms: Biologically Inspired and Population-Based Approaches to Computer Intelligence is an ideal text for advanced undergraduate students, graduate students, and professionals involved in engineering and computer science.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Hardcover","offer_id":45201803083927,"sku":"9780470937419","price":13148.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9780470937419.webp?v=1767307624","url":"https:\/\/atlanticbooks.com\/products\/evolutionary-optimization-algorithms-biologically-inspired-and-population-based-approaches-to-computer-intelligence-9780470937419","provider":"Atlantic Books","version":"1.0","type":"link"}